▷ (3 Days Left) Full Stack LLM Engineer

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include global corporations across multiple industries, national labs, and top-tier healthcare systems. In January, we announced a multi-year, multi-million-dollar partnership with Mayo Clinic, underscoring our commitment to transforming AI applications across various fields. In August, we launched Cerebras Inference, the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. About T he Role This teams' principal responsibility is to rapidly bring up state-of-the-art open-source models, frameworks and data engineering. Success in this role requires a system-minded generalist who thrives in fast-paced bringup environments and is comfortable working across the entire software stack. Your work will play a critical role in achieving unprecedented levels of performance, efficiency, and scalability for AI applications. Responsibilities Contribute to the end-to-end bring up of frameworks for RL, inference serving, ML models on Cerebras CSX systems. Work across the stack: model architecture translation, graph lowering, compiler optimizations, runtime integration, and performance tuning. Debug performance and correctness issues spanning model code, compiler IRs, runtime behavior, and hardware utilization. Propose and prototype improvements across tools, APIs, or automation flows to accelerate future bring ups. Skills & Qualifications Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field with 8 to 12 years’ experience. Comfort navigating the full AI toolchain: Python modelling code, compiler IRs, performance profiling, etc. Strong debugging skills across performance, numerical accuracy, and runtime integration. Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and familiarity with model internals (e.g., attention, MoE, diffusion). Proficiency in C/C++ programming and experience with low-level optimization. Strong background in optimization techniques, particularly those involving NP-hard problems. What We Offer Competitive salary and benefits package. Opportunities for professional growth and career advancement. A dynamic and innovative work environment. The chance to work on cutting-edge technologies and make a significant impact on the future of AI. Why Join Cerebras People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection  point in our business. Members of our team tell us there are five main reasons they joined Cerebras: Build a breakthrough AI platform beyond the constraints of the GPU. Publish and open source their cutting-edge AI research. Work on one of the fastest AI supercomputers in the world. Enjoy job stability with startup vitality. Our simple, non-corporate work culture that respects individual beliefs. Read our blog:  Five Reasons to Join Cerebras in 2025. Apply today and become part of the forefront of groundbreaking advancements in AI Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer.  We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.